Quantifying and managing uncertainties that occur when data-driven models such as those provided by AI and machine learning methods are applied is crucial. This whitepaper provides a brief motivation and first overview of the state of the art in identifying and quantifying sources of uncertainty for data-driven components as well as means for analyzing their impact.
@article{arxiv.1811.11669,
title = {Towards Identifying and Managing Sources of Uncertainty in AI and Machine Learning Models - An Overview},
author = {Michael Kläs},
journal= {arXiv preprint arXiv:1811.11669},
year = {2018}
}